[1] |
FIELD C B. Plant physiology of the “missing” carbon sink [J]. Plant Physiol, 2001, 125(1): 25 − 28. |
[2] |
XU Sixiao, ZHAO Xinqun, FU Yuling, et al. Characterizing CO2 fluxes for growing and non-growing seasons in a shrub ecosystem on the Qinghai-Tibet Plateau [J]. Sci China Ser D-Earth Sci, 2005, 48(suppl I): 133 − 140. |
[3] |
RUIMY A, JARVIS P G, BALDOCCHI D D, et al. CO2 fluxes over plant canopies and solar radiation: a review [J]. Adv Ecol Res, 1995, 26: 1 − 68. |
[4] |
CHEVALLIER J. Carbon futures and macroeconomic risk factors: a view from the EUETS [J]. Energy Econ, 2009, 31(4): 614 − 625. |
[5] |
徐小军,周国模,杜华强,等. 缺失数据插补方法及其参数估计窗口大小对毛竹林CO2通量估算的影响[J]. 林业科学, 2015, 51(9): 141 − 149.
XU Xiaojun, ZHOU Guomo, DU Huaqiang, et al. Effects of interpolation and window sizes in Phyllostachys edulis forest for parameter estimation on calculation of CO2 flux [J]. Sci Silv Sin, 2015, 51(9): 141 − 149. |
[6] |
徐小军,周国模,莫路锋,等. 一种面向下垫面不均一的森林碳通量监测方法[J]. 中国科学: 信息科学, 2013, 43(10): 1342 − 1352.
XU Xiaojun, ZHOU Guomo, MO Lufeng, et al. Study on carbon flux measurement using wireless sensor network under inhomogeneous surface condition [J]. Sci Sin Inf, 2013, 43(10): 1342 − 1352. |
[7] |
NOORMETS A, CHEN Jiqun, GU Lianhong, et al. The phenology of gross ecosystem productivity and ecosystem respiration in temperate hardwood and conifer chronosequences[M]//NOORMETS A. Phenology of Ecosystem Processes, New York: Springer, 2009: 59 − 85. |
[8] |
AUBINET M, VESALA T, PAPALE D. Eddy Covariance: A Practical Guide to Measurement and Data Analysis[M].[s. l.]: Springer Science & Business Media, 2012. |
[9] |
龚元,赵敏,姚鑫,等. 城市生态系统复合下垫面碳通量特征: 以上海市奉贤大学城为例[J]. 长江流域资源与环境, 2017, 26(1): 91 − 99.
GONG Yuan, ZHAO Min, YAO Xin, et al. Study on carbon flux characteristics of the underlying surface of urban ecosystem: a case study of Shanghai Fengxian University City [J]. Resour Environ Yangtze Basin, 2017, 26(1): 91 − 99. |
[10] |
龚元,郭智娟,张凯迪,等. 植被对亚热带城市生态系统CO2通量的影响[J]. 生态学报, 2019, 39(2): 530 − 541.
GONG Yuan, GUO Zhijuan, ZHANG Kaidi, et al. Impact of vegetation on CO2 flux of a subtropical urban ecosystem [J]. Acta Ecol Sin, 2019, 39(2): 530 − 541. |
[11] |
ZHANG Kun, LIU Naiwen, CHEN Yue, et al. Comparison of different machine learning method for GPP estimation using remote sensing data[C]// IOP. IOP Conference Series: Materials Science and Engineering.[s. l.]: IOP Publishing, 2019, 490(6): 062010. doi: 10.1088/1757-899X/490/6/062010. |
[12] |
NEY P, GRAF A, BOGENA H, et al. CO2 fluxes before and after partial deforestation of a central European spruce forest [J]. Agric For Meteorol, 2019, 274: 61 − 74. |
[13] |
PILLAI N D, NANDY S, PATEL N R, et al. Integration of eddy covariance and process-based model for the intra-annual variability of carbon fluxes in an Indian tropical forest [J]. Biodiversity Conserv, 2019, 28(6): 1 − 19. |
[14] |
KIM J H, HWANG T, SCHAAF C L, et al. Seasonal variation of source contributions to eddy-covariance CO2 measurements in a mixed hardwood-conifer forest [J]. Agric For Meteorol, 2018, 253/254: 71 − 83. |
[15] |
JOINER J, YOSHIDA Y, ZHANG Y, et al. Estimation of terrestrial global gross primary production (GPP) with satellite data-driven models and eddy covariance flux data [J]. Remote Sensing, 2018, 10(9): 1346. |
[16] |
KLJUN N, CALANCA P, ROTACH M W, et al. A simple two-dimensional parameterisation for flux footprint prediction (FFP) [J]. Geoscientif Mod Dev, 2015, 8(11): 3695 − 3713. |
[17] |
WOFSY S C, GOULDEN M L, MUNGER J W, et al. Net exchange of CO2 in a mid-latitude forest [J]. Science, 1993, 260(5112): 1314 − 1317. |
[18] |
NEFTEL A, SPIRIG C, AMMANN C. Application and test of a simple tool for operational footprint evaluations [J]. Environ Pollut, 2008, 152(3): 644 − 652. |
[19] |
SCHMID H P. Source areas for scalars and scalar fluxes [J]. Bound-Lay Meteorol, 1994, 67(3): 293 − 318. |
[20] |
LANDSBERG J J, WARING R H. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning [J]. For Ecol Manage, 1997, 95(3): 209 − 228. |
[21] |
LLOYD J, TAYLOR J A. On the temperature dependence of soil respiration [J]. Funct Ecol, 1994, 8(3): 315 − 323. |
[22] |
PILEGAARD K, HUMMELSHØJ P, JENSEN N O, et al. Two years of continuous CO2 eddy-flux measurements over a Danish beech forest [J]. Agric For Meteorol, 2001, 107(1): 29 − 41. |
[23] |
PITA G, GIELEN B, ZONA D, et al. Carbon and water vapor fluxes over four forests in two contrasting climatic zones [J]. Agric For Meteorol, 2013, 180: 211 − 224. |
[24] |
GU Lianhong, POST W M, BALDOCCHI D D, et al. Characterizing the seasonal dynamics of plant community photosynthesis across a range of vegetation types[M]//NOORMETS A. Phenology of Ecosystem Processes. New York: Springer, 2009: 35 − 58. |
[25] |
BRACHO R, STARR G, GHOLZ H L, et al. Controls on carbon dynamics by ecosystem structure and climate for southeastern U.S. slash pine plantations [J]. Ecol Monogr, 2012, 82(1): 101 − 128. |
[26] |
BESNARD S, CARVALHAIS N, ARAIN M A, et al. Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests[J]. PLoS One, 2019, 14(2): e0211510. doi: 10.1371/journal.pone. 0211510. |
[27] |
纪小芳,鲁建兵,杨军,等. 凤阳山针阔混交林碳通量变化特征及其影响因子[J]. 东北林业大学学报, 2019, 47(3): 49 − 55.
JI Xiaofang, LU Jianbing, YANG Jun, et al. Carbon flux variation characteristics and its influencing factors in coniferous and broad-leaved mixed forest in Fengyang Mountain [J]. J Northeast For Univ, 2019, 47(3): 49 − 55. |
[28] |
王春林,于贵瑞,周国逸,等. 鼎湖山常绿针阔叶混交林CO2通量估算[J]. 中国科学D辑: 地球科学, 2006, 36(suppl 1): 119 − 129.
WANG Chunlin, YU Guirui, ZHOU Guoyi, et al. CO2 flux evaluation over the evergreen coniferous and broad-leaved mixed forest in Dinghushan, China [J]. Sci China Ser D Earth Sci, 2006, 36(suppl 1): 119 − 129. |
[29] |
BALDOCCHI D. Flux footprints within and over forest canopies [J]. Bound-Lay Meteorol, 1997, 85(2): 273 − 292. |
[30] |
金莹,张志强,方显瑞,等. 杨树人工林生态系统通量贡献区分析[J]. 生态学报, 2012, 32(12): 3966 − 3974.
JIN Ying, ZHANG Zhiqiang, FANG Xianrui, et al. Footprint analysis of turbulent flux over a poplar plantation in Northern China [J]. Acta Ecol Sin, 2012, 32(12): 3966 − 3974. |
[31] |
龚笑飞,陈丽萍,莫路锋. 基于FSAM模型的毛竹林碳通量贡献区研究[J]. 西南林业大学学报, 2015, 35(6): 37 − 44.
GONG Xiaofei, CHEN Liping, MO Lufeng. Research of flux footprint of anji bamboo forest ecosystems based on the FSAM model [J]. J Southwest For Univ, 2015, 35(6): 37 − 44. |
[32] |
OGUNJEMIYO S O, KAHARABATA S K, SCHUEPP P H, et al. Methods of estimating CO2, latent heat and sensible heat fluxes from estimates of land cover fractions in the flux footprint [J]. Agric For Meteorol, 2003, 117(3/4): 125 − 144. |
[33] |
张慧. 中亚热带人工林碳水通量贡献区的评价研究[D]. 南京: 南京信息工程大学, 2012.
ZHANG Hui. The Study of Flux Footprint in Typical Subtropical Monsoon Man-Planted Forest[D]. Nanjing: Nanjing University of Information Science and Technology, 2012. |
[34] |
唐祥,陈文婧,李春义,等. 北京八达岭林场人工林净碳交换及其环境影响因子[J]. 应用生态学报, 2013, 24(11): 3057 − 3064.
TANG Xiang, CHEN Wenjing, LI Chunyi, et al. Net carbon exchange and its environmental affecting factors in a forest plantation in Badaling, Beijing of China [J]. Chin J Appl Ecol, 2013, 24(11): 3057 − 3064. |
[35] |
WANG Weiguo, DAVIS K J. A numerical study of the influence of a clearcut on eddy-covariance fluxes of CO2 measured above a forest [J]. Agric For Meteorol, 2008, 148(10): 1488 − 1500. |
[36] |
李小梅,张秋良. 兴安落叶松林生长季碳通量特征及其影响因素[J]. 西北农林科技大学学报: 自然科学版, 2015, 43(6): 121 − 128.
LI Xiaomei, ZHANG Qiuliang. Carbon flux and its impact factors of Larix gmelinii forest ecosystem during growing season [J]. J Northwest A&F Univ Nat Sci Ed, 2015, 43(6): 121 − 128. |
[37] |
牛晓栋,江洪,张金梦,等. 浙江天目山老龄森林生态系统CO2通量特征[J]. 应用生态学报, 2016, 27(1): 1 − 8.
NIU Xiaodong, JIANG Hong, ZHANG Jinmeng, et al. Characteristics of CO2 flux in an old growth mixed forest in Tianmu Mountain, Zhejiang, China [J]. Chin J Appl Ecol, 2016, 27(1): 1 − 8. |
[38] |
张一平,沙丽清,于贵瑞,等. 热带季节雨林碳通量年变化特征及影响因子初探[J]. 中国科学D辑: 地球科学, 2006, 36(suppl 1): 139 − 152.
ZHANG Yiping, SHA Liqing, YU Guirui, et al. Annual variation of carbon flux and impact factors in the tropical seasonal rain forest of Xishuangbanna, SW China [J]. Sci China Ser D Earth Sci, 2006, 36(suppl 1): 139 − 152. |
[39] |
LIU Yunfen, SONG Xia, YU Guirui, et al. Seasonal variation of CO2 flux and its environmental factors in evergreen coniferous plantation [J]. Sci China Ser D Earth Sci, 2005, 48(suppl 1): 123 − 132. |
[40] |
TUCKER C J, PINZON J E, BROWN M E, et al. An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data [J]. Int J Remote Sens, 2005, 26(20): 4485 − 4498. |
[41] |
RICHARDSON A D, BLACK T A, CIAIS P, et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity [J]. Philos Trans Roy Soc B Biol Sci, 2010, 365(1555): 3227 − 3246. |
[42] |
NIU Shuli, FU Yuling, GU Lianhong, et al. Temperature sensitivity of canopy photosynthesis phenology in northern ecosystems[C]//SCHWARTZ M. Phenology: An Integrative Environmental Science. Dordrecht: Springer, 2013: 503 − 519. |
[43] |
GONSAMO A, CHEN J M, PRICE D T, et al. Land surface phenology from optical satellite measurement and CO2 eddy covariance technique [J]. J Geophys Res Biogeosci, 2012, 117(G3): 1 − 18. |
[44] |
LIPOVETSKY S. Double logistic curve in regression modeling [J]. J Appl Statist, 2010, 37(11): 1785 − 1793. |
[45] |
MANCUSO S, PASQUALI G, FIORINO P. Phenology modelling and forecasting in olive (Olea europaea L.) using artificial neural networks [J]. Adv Hortic Sci, 2002, 16(3): 155 − 164. |
[46] |
PAPALE D, VALENTINI R. A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization [J]. Global Change Biol, 2003, 9(4): 525 − 535. |
[47] |
HE Honglin, YU Guirui, ZHANG Leiming, et al. Simulating CO2 flux of three different ecosystems in China FLUX based on artificial neural networks [J]. Sci China Ser D Earth Sci, 2006, 49(2): 252 − 261. |
[48] |
唐欢,李振旺,丁蕾,等. 基于地面涡度数据的中国草原区GPP遥感产品验证[J]. 草业科学, 2018, 35(11): 2568 − 2583.
TANG Huan, LI Zhenwang, DING Lei, et al. Validation of GPP remote sensing products using eddy covariance flux observations in the grassland area of China [J]. Pratac Sci, 2018, 35(11): 2568 − 2583. |
[49] |
杜启勇,林爱文,付醒. 基于遥感和美国碳通量观测数据的GPP模型比较研究[J]. 测绘与空间地理信息, 2018, 41(2): 138 − 141, 146.
DU Qiyong, LIN Aiwen, FU Xing. Comparison of multiple GPP models using remote sensing and American carbon flux data [J]. Geomat Spat Inf Technol, 2018, 41(2): 138 − 141, 146. |
[50] |
刘啸添,周蕾,石浩,等. 基于多种遥感植被指数、叶绿素荧光与CO2通量数据的温带针阔混交林物候特征对比分析[J]. 生态学报, 2018, 38(10): 3482 − 3494.
LIU Xiaotian, ZHOU Lei, SHI Hao, et al. Phenological characteristics of temperate coniferous and broad-leaved mixed forests based on multiple remote sensing vegetation indices, chlorophyll fluorescence and CO2 flux data [J]. Acta Ecol Sin, 2018, 38(10): 3482 − 3494. |
[51] |
史桂芬,贺伟光. 涡度相关技术在农田生态系统通量研究中的应用[J]. 现代农业科技, 2019(6): 141 − 143.
SHI Guifen, HE Weiguang. Application of eddy covariance technology in flux research of farmland ecosystem [J]. Mod Agric Sci Technol, 2019(6): 141 − 143. |
[52] |
同小娟,张劲松,孟平. 基于涡度相关法的森林生态系统碳交换及其控制机制[J]. 温带林业研究, 2018, 1(2): 1 − 9, 14.
TONG Xiaojuan, ZHANG Jinsong, MENG Ping. Carbon exchange between forest ecosystems and the atmosphere and its control mechanisms based on the eddy covariance method [J]. J Temp For Res, 2018, 1(2): 1 − 9, 14. |
[53] |
LAI Chunta, KATUL G, OREN R, et al. Modeling CO2 and water vapor turbulent flux distributions within a forest canopy [J]. J Geophys Res Atmos, 2000, 105(D21): 26333 − 26351. |
[54] |
MEDLYN B E, ROBINSON A P, CLEMENT R, et al. On the validation of models of forest CO2 exchange using eddy covariance data: some perils and pitfalls [J]. Tree Physiol, 2005, 25(7): 839 − 857. |
[55] |
BALDOCCHI D D, WILSON K B. Modeling CO2 and water vapor exchange of a temperate broadleaved forest across hourly to decadal time scales [J]. Ecol Mod, 2001, 142(1/2): 155 − 184. |
[56] |
PARK H, IIJIMA Y, YABUKI H, et al. The application of a coupled hydrological and biogeochemical model (CHANGE) for modeling of energy, water, and CO2 exchanges over a larch forest in eastern Siberia [J]. J Geophys Res Atmos, 2011, 116: D15102. |
[57] |
XIE Zhenghui, WANG Linying, JIA Binghao, et al. Measuring and modeling the impact of a severe drought on terrestrial ecosystem CO2 and water fluxes in a subtropical forest [J]. J Geophys Res Biogeosci, 2016, 121(10): 2576 − 2587. |
[58] |
CHEN Xiongwen. Modeling the effects of global climatic change at the ecotone of boreal larch forest and temperate forest in northeast China [J]. Clim Change, 2002, 55(1/2): 77 − 97. |
[59] |
SHI Tingting, GUAN Dexin, WANG Anzhi, et al. Modeling canopy CO2 and H2O exchange of a temperate mixed forest [J]. J Geophys Res Atmos, 2010, 115(D7): D17117. |
[60] |
李雪建,毛方杰,杜华强,等. 双集合卡尔曼滤波LAI同化结合BEPS模型的竹林生态系统碳通量模拟[J]. 应用生态学报, 2016, 27(12): 3797 − 3806.
LI Xuejian, MAO Fangjie, DU Huaqiang, et al. Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter [J]. Chin J Appl Ecol, 2016, 27(12): 3797 − 3806. |
[61] |
陈晨,沃文伟,范文义. 森林生态系统碳循环模型参数优化[J]. 东北林业大学学报, 2016, 44(5): 15 − 19.
CHEN Chen, WO Wenwei, FAN Wenyi. Optimization of ecosystem carbon cycle model parameters [J]. J Northeast For Univ, 2016, 44(5): 15 − 19. |
[62] |
杨延征,马元丹,江洪,等. 基于IBIS模型的1960−2006年中国陆地生态系统碳收支格局研究[J]. 生态学报, 2016, 36(13): 3911 − 3922.
YANG Yanzheng, MA Yuandan, JIANG Hong, et al. Evaluating the carbon budget pattern of Chinese terrestrial ecosystem from 1960 to 2006 using Integrated Biosphere Simulator [J]. Acta Ecol Sin, 2016, 36(13): 3911 − 3922. |
[63] |
王萍. 基于IBIS模型的东北森林净第一性生产力模拟[J]. 生态学报, 2008, 29(6): 3213 − 3220.
WANG Ping. Simulation of forest net primary productivity in northeastern China with IBIS [J]. Acta Ecol Sin, 2008, 29(6): 3213 − 3220. |
[64] |
王培娟,谢东辉,张佳华,等. 长白山森林植被NPP主要影响因子的敏感性分析[J]. 地理研究, 2008, 27(2): 323 − 331.
WANG Peijuan, XIE Donghui, ZHANG Jiahua, et al. Sensitivity analysis for primary factors of the forest net primary productivity in Changbaishan Natural Reserve based on process model [J]. Geogr Res, 2008, 27(2): 323 − 331. |